A pattern recognition system, such as a speech recognition system, takes an input signal and attempts to decode the signal to find a pattern represented by the signal. For example, in a speech recognition system, a speech signal is received by the recognition system and is decoded to identify a string of words represented by the speech signal.
Acoustic processing in current speech recognition systems includes two parts: a front end that extracts acoustic features of the signal and a back end acoustic model that scores hypotheses of sequences based on the acoustic features. Training of parameters that define the front end and back end are done separately, which can lead to a less than optimal speech recognition system.
The discussion above is merely provided for general background information and is not intended to be used as an aid in determining the scope of the claimed subject matter.